How I Made Money with AI Music in 30 Days (and How You Can Too)

on 9 hours ago

How I Made Money with AI Music in 30 Days (and How You Can Too)

AI music is one of the most exciting — and controversial — developments in the creative industry right now. Artists like Bad Bunny and Billie Eilish have voiced concerns about its impact on musicians’ careers. But no matter where you stand on the debate, one thing is clear: AI music is here to stay, and it’s getting better every day.

I’ve always loved music and business, so I decided to run a 30-day experiment to see if regular people like you and me could actually make money with AI-generated tracks. The results surprised me — and they might change how you think about the music industry.

In this post, I’ll walk you through:

How to find the right market
How to create AI music that people actually want
How to distribute it …and of course, my 30-day earnings report.

Step 1: Find the Right Market

This was the most important part of the experiment. Simply creating random tracks and uploading them is a recipe for failure — 100,000 songs hit Spotify daily, and 3.7 million videos are uploaded to YouTube every day. If you don’t stand out, your music will disappear in the noise.

Instead, I focused on uploading music people are already searching for. To figure that out, I used a market research tool called Ahrefs, which shows what people search for on Google. Why Google? Because YouTube, Spotify, and even the App Store are also search-driven platforms. Google data can be a strong indicator of demand everywhere.

Here’s what I did:

Searched for * music keywords (e.g., “Christmas music,” “classical music,” “calming music”).
Identified consistent, year-round niches: for example, “gaming music” and “baby sleep music.”
Listened to examples on YouTube to understand the style — gaming music turned out to be mostly intense EDM or dubstep, while baby sleep music is slow, calming, and repetitive.

Key takeaway: Don’t guess. Use search data to find proven demand before you create.

Step 2: Create AI Music That Fits the Market

For production, I tested two leading AI music platforms: Suno and Udio. Both are free to try, but I preferred Suno for this project — it delivered more professional-sounding and unique tracks.

Here’s my process:

Create an account on Suno.
Switch to instrumental mode.
Enter a specific prompt, e.g., EDM dubstep gaming music.
Generate multiple tracks and use the “extend” feature to make them longer than 2 minutes.
Select around 20 tracks that match the intended vibe and compile them into an album.

If you want to experiment with lyric-based AI tracks, you can also try tools like lyricstosongai.com — it lets you turn text lyrics into complete AI-generated songs, making it easy to create vocal music for albums, ads, or YouTube content.

Step 3: Design Your Album Artwork

Visuals matter — especially on platforms like Spotify. I noticed that top gaming music albums had war-inspired or anime-style covers.

My method:

Use AI image generation (via ChatGPT plugins or other tools) to create a “video game war” style cover.
Edit in Canva, add an artist name and album title, and export as a high-resolution PNG (1500×1500 pixels or larger).

Step 4: Distribute Your Album

I used EmuBands for this example, but you can choose from many distributors like DistroKid, TuneCore, or Amuse. The steps are straightforward:

Create an account
Upload your album bundle
Fill in metadata (artist name, tracklist, genre)
Submit for release

Pro tip: I upload albums through multiple distributors to reduce risk. Unfortunately, I’ve experienced issues with certain distributors not paying royalties, so diversifying is smart.

My 30-Day Results

I uploaded two albums:

A gaming music album
A baby sleep music album

I did zero promotion. The idea was to let market demand (discovered through research) drive organic discovery.

The outcome:

Nearly 35,000 Spotify streams in the first month.
Earnings: $83+ in royalties.
Streams grew from just 1/day on launch to 3,400/day by the end of the month.

Yes, I got lucky with a hit album on the first try — but realistically, expect to create 5–10 albums before landing a consistent winner.

Final Thoughts

Making money with AI music isn’t about chasing random creative ideas — it’s about combining data-driven market research with smart use of AI tools.

If you want to try this yourself:

Use keyword tools to find music niches people are already searching for.
Use AI platforms like Suno, Udio, or lyricstosongai.com to quickly produce quality tracks.
Distribute through multiple channels and let the audience find you.

The future of music will likely be a blend of human creativity and AI efficiency — and those who adapt early stand to benefit the most.